[[missing key: loading-pdf-error]] [[missing key: loading-pdf-link]]
Abstract
Rice is amongst the majorly cultivated crops in India and its leaf diseases can have a substantial impact on output and quality. The most important component is identifying rice leaf diseases, which have a direct impact on the economy and food security. Brown spot, Leaf Blast, Hispa are the most frequently occurring rice leaf diseases. To resolve this issue, we have studied various machine learning and deep learning approaches for detecting the diseases on their leaves by calculating their accuracy, recall, and precision to measure the performance. This study helps the farmers by detecting the diseases in rice leaves in order to get a healthy crop yield. The deep learning models perform well when compared with the machine learning methods. After analyzing all of the deep learning models, we found that the 5-layer convolution model had the best accuracy of 78.2 %, while others, such as VGG16, had a lower accuracy of 58.4%.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details
1 DEPARTMENT OF INFORMATION TECHNOLOGY NATIONAL INSTITUTE OF TECHNOLOGY , RAIPUR